When they are queried in the right way, numbers can give us a wealth of information that is crucial to a company’s very survival. The spreadsheet is fundamental in every phase of the data analyst’s work on and handling of data. Data and spreadsheet go hand in hand. There are many tools used to query data, but they always go and fish it out of our much-loved spreadsheet.
The most widely used tool is Python, one of the best-known programming languages in the world, which through lines of code lets you work on data precisely and immediately.
Let us look together at what exactly a data analyst does.
The crucial role of the data analyst
You might think that the data analyst is someone who works with their head bent over a desk. Nothing could be more wrong! On the contrary, the data analyst is a professional who constantly deals with all those people who can provide the tools and material needed to create the dataset.
The various phases of a data analyst’s work
The creation of a clean, error-free and well-organised dataset is the very first tile of the mosaic which, if placed well, makes all the rest of the work simpler. After filling our nice worksheet with all the data needed to create the dataset, the data analyst will try to clean it, making it understandable and easy to read even for non-specialists.
Once this first phase is over, the data analyst will try to analyse the dataset and take a snapshot of the situation at that particular moment in the life of a company, identifying recurring trends: this phase is called “data analysis”.
The last phase of the work, also called “data analytics”, serves to guarantee a strategic use of data. Data analytics makes it possible to query the data and, once the answers have been grasped, to make forecasts by creating charts and diagrams. It is an essential phase for increasing business opportunities and therefore the turnover of the companies themselves, as well as for managing the overabundance of data that results from the digitalisation of the various company processes.
The applications for companies can be many: after a careful analysis of the dataset, it is possible to determine the specific needs, perhaps never thought through until that moment, and create software that can actually be useful.
dotenv can therefore support customers in this decision-making phase. Because, to paraphrase a famous saying, “Render unto Caesar the things that are Caesar’s, but give the data to the data analyst”.